Big Data
Drills and Deep-Dives: UI Patterns for Big Data
How do you show 1 million records without crashing the browser? This lesson covers breadcrumb navigation and filtered aggregation for big data UIs.
Level: IntermediateBig Data
What You'll Learn
Virtual scrolling & windowed rendering for large datasets
Server-side pagination and aggregation
Breadcrumb drill-down navigation pattern
Click-to-Filter interaction design
D3.js and Chart.js for interactive filtering
Debouncing and query optimisation for filters
Building responsive big data dashboards
What's Included
🧭AI Tutor🔒
Interactive learning path with AI-generated lessons read aloud by your personal tutor
🧪Practice Lab🔒
Step-by-step lab instructions with AI guidance — run in your own IDE or sandbox.
🎙️Mock Interviews🔒
AI interviewer asks tailored questions, gives real-time feedback and a score report
📝Evaluation🔒
MCQ questions (theory, practical, code) to test your knowledge and earn a badge
⚔️Challenge AI🔒
Compete head-to-head against AI on real production problems — judged on correctness, performance, scalability, code quality, and edge cases
Course Syllabus
Module 1: The Big Data UI Problem
- •Why rendering 1M rows crashes the browser
- •Virtual scrolling with react-window or TanStack Virtual
- •Server-side aggregation vs client-side filtering
- •Pagination patterns: cursor, offset, keyset
- •UX trade-offs: speed vs completeness
Module 2: Drill-Down Navigation
- •Breadcrumb pattern for hierarchical data
- •Zoomable charts: continent → country → city
- •Click event handling in D3.js
- •Maintaining filter state in the URL
- •Back-button behaviour for drill navigation
Module 3: Click-to-Filter Implementation
- •Building faceted filters with Chart.js
- •Debouncing filter requests to the backend
- •Cross-chart filter propagation
- •Animated transitions between filter states
- •Capstone: interactive sales analytics dashboard
You're all set
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✓Practice Lab
✓Mock Interviews
✓Evaluation
✓Challenge AI